3 papers
cs.LG2023
Concrete Safety for ML Problems: System Safety for ML Development and Assessment
Edgar W. Jatho, Logan O. Mailloux, Eugene D. Williams +2
Many stakeholders struggle to make reliances on ML-driven systems due to the risk of harm these systems may cause. Concerns of trustworthiness, unintended social harms, and unaccep…
cs.LG2022
System Safety Engineering for Social and Ethical ML Risks: A Case Study
Edgar W. Jatho, Logan O. Mailloux, Shalaleh Rismani +2
Governments, industry, and academia have undertaken efforts to identify and mitigate harms in ML-driven systems, with a particular focus on social and ethical risks of ML component…
cs.HC2022
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML
Shalaleh Rismani, Renee Shelby, Andrew Smart +4
Inappropriate design and deployment of machine learning (ML) systems leads to negative downstream social and ethical impact -- described here as social and ethical risks -- for use…